New Study Suggests Apple Watch Heart Rate Sensor Can Predict COVID-19 Up to a Week Before a Swab Test

A new study by Mount Sinai researchers has found that an Apple Watch can effectively predict a positive COVID-19 diagnosis up to a week before current PCR-based nasal swab tests (via TechCrunch).

mount sinai covid apple watch study
Published in the peer-reviewed Journal of Medical Internet Research, the "Warrior Watch Study" involved several hundred Mount Sinai healthcare workers using a dedicated Apple Watch and iPhone app for personal health data monitoring and collection.

All participants were also required to fill out a daily survey over several months to provide direct feedback about potential coronavirus symptoms and other factors, including stress.

The data collection ran from April through September, and the main point of focus for researchers was heart rate variability (HRV), a key indicator of strain on the nervous system. This data point was combined with reported symptoms associated with the disease, such as fever, aches, dry cough, and loss of taste and smell.

The Warrior Watch Study was not only able to predict infections up to a week before tests provided confirmed diagnoses, but also revealed that participants' HRV patterns normalized fairly quickly after their diagnosis, returning to normal roughly one to two weeks following their positive tests.

The researchers hope that the results can help anticipate outcomes and remotely isolate individuals from others who are at risk, without having to perform a physical exam or administer a swab test, preventing potential spread before someone is highly contagious.

According to TechCrunch, the study will in future expand in order to look at what other wearables can reveal about the impact of COVID-19 on the health of health care workers, including how things like sleep and physical activity may relate to the disease.

In related research that is ongoing, Apple is currently partnering with investigators at the Seattle Flu Study and faculty at the University of Washington's School of Medicine to explore how changes in blood oxygen and heart rate can be early signals of the onset of influenza and COVID-19.

Previous independent Apple Watch studies have shown that the smartwatch's heart sensors may be able to detect early signs of diabetes and provide early warning signs of atrial fibrillation.

Related Roundup: Apple Watch Series 9
Buyer's Guide: Apple Watch (Neutral)

Top Rated Comments

ethanwa79 Avatar
40 months ago
The Apple Watch could very well end up being one of the most significant medical devices ever made in human history, especially if they end up adding blood-sugar monitoring and more early warning diagnosis like this COVID-19 study. Could end up saving countless lives from all kinds of various conditions.
Score: 30 Votes (Like | Disagree)
wesley96 Avatar
40 months ago
It’s amazing how much heartbeats tell us.
Score: 17 Votes (Like | Disagree)
svanstrom Avatar
40 months ago

Surely it's "predicting" any illness? I know runners who regularly wear HRMs have ben using this fact for years. Resting heart rate higher than usual? Heart rate noticeably higher than usual when doing a typical workout? Body is probably fighting something. Or that pre-workiut double espresso has yet to work its way through your system.

I guess the news here is the amount of people now wearing HRMs, which is a good thing.
Yes, it predicts a wide range of [somethings]; which could be an infection, stress, not enough sleep, and so on.

But, whatever the cause is, the warning is valid.

Think of is as a warning light in your car; you can probably keep on driving like normal, but if you do you potentially take the problem from a quick fix all the way to a complete failure/crash/burnout.

What we're seeing now is that people wearing heart/health monitors like these makes it possible to turn on these warning lights waaay before they were noticed in the past.

So let's extrapolate from this, and guess a future feature that might be possible due to these findings:

The current Covid-19 apps focuses on tracking outbreaks, alerting those that potentially have been exposed; but imagine if these apps could use the heart rate data to tell people, long before they feel it themselves, that they just in case should stay at home.

We're talking about, based on what they say here, potentially a whole week of a spreader being out of the system.

Potentially this could in an anonymised format also be reported to the local health authorities; making it possible to predict major outbreaks based on the population's heart rates. They could even prepare/stand down healthcare services by predicting what will/might happen a week into the future; making it much easier to not burnout the healthcare workers.

These watches, combined with the magic of scientists, could be amazingly revolutionary.
Score: 14 Votes (Like | Disagree)
sorgo † Avatar
40 months ago
Wow, this is pretty massive news if accurate. Hopefully the technology continues to be put to use in a relatively benign and progressive way that builds upon not only warning someone of the possibility of a potential coronavirus case but of other maladies as well—all while, most importantly, protecting user privacy with the utmost earnestness.
Score: 8 Votes (Like | Disagree)
AlexESP Avatar
40 months ago
In fact covid and many more things. I’ve always seen my resting HR rise before I actually get sick, and with covid it was the same. But yes, specifically for this one it’s surprising how quickly it decreased from peak (75) to absolutely normal (45) in one day.



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Score: 8 Votes (Like | Disagree)
adrianlondon Avatar
40 months ago
Surely it's "predicting" any illness? I know runners who regularly wear HRMs have ben using this fact for years. Resting heart rate higher than usual? Heart rate noticeably higher than usual when doing a typical workout? Body is probably fighting something. Or that pre-workiut double espresso has yet to work its way through your system.

I guess the news here is the amount of people now wearing HRMs, which is a good thing.
Score: 5 Votes (Like | Disagree)

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